Traditionally, evaluating the outcome (effect) of behaviour change interventions in household energy studies have been given far more importance than studying the underlying processes that is assumed to have led to the outcome.
9 September 2016
Traditionally, evaluating the outcome (effect) of behaviour change interventions in household energy studies have been given far more importance than studying the underlying processes that is assumed to have led to the outcome.
| Traditional | Dynamic |
|---|---|
| cross sectional data | intensive longitudinal data |
| static relationships | underlying processes |
| (mostly) confirmatory | exploratory and confirmatory |
| multiple regressions | time series and dynamic models |
| SGR | Buurkracht |
|---|---|
| N = 100 (households) | N = 142 (neighbourhoods) |
| t = 2 years (2013 - 2015) | t = 2 years (starting Dec 2015) |
| feedback, demand side management | feedback, adoption of PV |
| baseline (3 months) | baseline (6 months) |
| non equivalent control group | non equivalent control group |
The Data Box (Catell, 1952)
Psychological determinants of household energy consumption
\(y_n = c + \sum_{i=1}^{p}\phi_{i}y_{n-i} + \sum_{i=1}^{p}\theta_{i}\epsilon_{n-i} + \epsilon_n\)
| Model | AIC | BIC |
|---|---|---|
| ARIMA(1,0,2) | 312261.9 | 312302.6 |
| HMM (k=3) | 301502.2 | 301618.7 |
When comparing models fitted by maximum likelihood to the same data, the smaller the AIC or BIC, the better the fit.
Thank you